Evaluation of the Direct Interaction between Amino Acids and Glutathione-Coated CdTe Quantum Dots and Application in Urinalysis for Histidine Determination
Bibliographic record
Abstract
The present work aimed to direct amino acid (AA) sensing by quantum dots (QD) and development of an analytical method for potential fast clinical tests. Notably, AA with a positive charge or neutral polar chains, namely L-histidine (His) and L-threonine (Thr), responded to glutathione-coated CdTe (GSH-CdTe) (F 90%, variation of fluorescence intensity). However, in ammoniacal buffer (0.25 mol L -1 ) at pH 8.0, 2.2 nm GSH-CdTe responded only to His. Static quenching with complex association constant (K sv ) varying from 2.81 to 0.94 (10 L mol -1 ) as well as van der Waals forces and/or hydrogen bonding were predicted for His-QD quenching mechanism and binding type. Additionally, thermodynamic parameters as H = -76.5 kJ mol -1 (enthalpy), S = -227.4 J K -1 mol -1 (entropy) and G from -9.8 until -6.4 kJ mol -1 (Gibbs free energy) at 20 to 35 C were estimated by van't Hoff equation. Under optimal conditions, the developed method presented a linear range from 0.42 to 35 mmol L -1 (with correlation coefficient (r) of 0.9970, n = 7), good precision (relative standard deviations (RSD) < 2.5% for 2.5 and 20 mmol L -1 ; n = 6) and limit of detection 1.6 10 -4 mol L -1 (0.025 mg mL -1 ). Recovery tests were performed on artificial urine and human urine samples with recoveries ranging from 78.7 to 127.6%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".